A system for predicting and summarizing medical events from electronic health records includes a computer memory storing aggregated electronic health records from a multitude of patients of diverse age, health conditions, and demographics including medications, laboratory values, diagnoses, vital signs, and medical notes. The aggregated electronic health records are converted into a single standardized data structure format and ordered arrangement per patient, e.g., into a chronological order. A computer (or computer system) executes one or more deep learning models trained on the aggregated health records to predict one or more future clinical events and summarize pertinent past medical events related to the predicted events on an input electronic health record of a patient having the standardized data structure format and ordered into a chronological order. An electronic device configured with a healthcare provider-facing interface displays the predicted one or more future clinical events and the pertinent past medical events of the patient.
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2. The system of claim 1, wherein the aggregated health records comprise health records arranged in different data formats.
3. The system of claim 1, wherein the standardized data structure format comprises Fast Health Interoperability Resources (FHIR).
4. The system of claim 1, wherein the aggregated health records contain hospitalization diagnoses, and wherein the diagnoses are mapped to single-level Clinical Classification Software (CCS) codes.
5. The system of claim 1, wherein combining the time embedding matrix with the product of the projection matrix and the data embedding matrix to generate the attention vector comprises using a column dot product operator to multiply the product of the projection matrix and the data embedding matrix with the time embedding matrix.
7. The method of claim 6, wherein the standardized data structure format comprises Fast Health Interoperability Resources (FHIR).
8. The method of claim 7, wherein the set of electronic health records includes both structured data and unstructured data including free text notes.
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August 30, 2017
August 9, 2022
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